How has the increase of Automated Trading Systems (ATS) influenced the futures market?
\[ \text{Performance} = \text{Skill} \times \sqrt{\text{Breadth}} \]
Two extremes
Single bet: \(0.51 \times 1000 + 0.49 \times (-1000) = 20\)
Multi bet: \(1000 \times [0.51 + 0.49 \times (-1)] = 20\)
The same expected return
Single bet: 49%
Multi bet: \(0.49 \times 0.49 \times \dots \times 0.49 = 0.49^{1000} \approx 0\)
\[ \text{risk} := \text{std}\left\{1,-1,-1,1, \dots, 1 \right\} = 1 \]
\[ \begin{align} \text{risk} &:= \text{std}\left\{1000,0,0,0, \dots, 0 \right\} = 31.62 \\ \text{risk} &:= \text{std}\left\{-1000,0,0,0, \dots, 0 \right\} = 31.62 \end{align} \]
Just like Sharpe Ratio
Single bet: \(\text{SR}_{\text{single}} = \frac{20}{31.62} =0.63\)
Multi bet: \(\text{SR}_{\text{multiple}} = \frac{20}{1} =20\)
\(20 = 0.63 \times \sqrt{1000}\)
\(\text{SR}_{\text{multiple}} = \text{SR}_{\text{single}} \times \sqrt{\text{Bets}}\)
\(\text{Performance} = \text{Skill} \times \sqrt{\text{Breadth}}\)
We use insights gained from years of fundamental trading to inspire bespoke quantitative strategies that are applied to a large collection of commodity markets



How to obtain a stationary time series







| Statistic | BB1 | BB1 live | BB2 | BB2 live |
|---|---|---|---|---|
| Annualized Return | 5.480 | -0.160 | 19.210 | 7.040 |
| Annualized Sharpe (Rf=0%) | 0.662 | -0.024 | 1.239 | 1.600 |
| Annualized Std Dev | 8.270 | 6.770 | 15.500 | 4.400 |
| Average Negative Month Return | -1.608 | -1.091 | -2.792 | -0.437 |
| Average Positive Month Return | 1.920 | 1.085 | 4.515 | 0.772 |
| Maximum Drawdown | 26.683 | 7.808 | 39.529 | 1.740 |
| Maximum Drawdown/Annualized Return | 4.869 | -48.799 | 2.058 | 0.247 |
| Number of Negative Months | 102.000 | 6.000 | 98.000 | 2.000 |
| Number of Positive Months | 149.000 | 6.000 | 151.000 | 8.000 |
Literature on extracting carry from futures:
Literature on applying machine learing techniques in algorithmic trading:
Aim of a trend following strategy
If we feed our trend system fake trendy data
can we trade it profitably?




| variable | TR1 | TR1 live |
|---|---|---|
| Annualized Return | 18.930 | 6.810 |
| Annualized Std Dev | 17.800 | 15.130 |
| Annualized Sharpe (Rf=0%) | 1.064 | 0.450 |
| Maximum Drawdown | 26.683 | 9.072 |
| Maximum Drawdown/Annualized Return | 1.410 | 1.332 |
| Number of Positive Months | 147.000 | 5.000 |
| Number of Negative Months | 103.000 | 3.000 |
| Average Positive Month Return | 5.383 | 3.910 |
| Average Negative Month Return | -3.573 | -4.897 |
In-house Research:
Strategy not yet live.
Strategy not yet live.


| Statistic | 1998- | 2008- | 2015- | live |
|---|---|---|---|---|
| Annualized Return | 13.570 | 12.490 | 2.360 | 3.980 |
| Annualized Sharpe (Rf=0%) | 1.083 | 0.997 | 0.258 | 0.695 |
| Annualized Std Dev | 12.530 | 12.530 | 9.130 | 5.730 |
| Average Negative Month Return | -2.224 | -2.149 | -1.874 | -1.171 |
| Average Positive Month Return | 3.855 | 3.950 | 2.258 | 1.374 |
| Maximum Drawdown | 25.575 | 25.575 | 14.132 | 4.068 |
| Maximum Drawdown/Annualized Return | 1.885 | 2.048 | 5.988 | 1.022 |
| Number of Negative Months | 113.000 | 64.000 | 26.000 | 5.000 |
| Number of Positive Months | 144.000 | 73.000 | 27.000 | 7.000 |

| Statistic | S&P500 | PSQCF | PSQCF and S&P500 |
|---|---|---|---|
| Annualized Return | 5.760 | 14.090 | 9.700 |
| Annualized Sharpe (Rf=0%) | 0.380 | 0.938 | 0.938 |
| Annualized Std Dev | 15.140 | 15.030 | 10.340 |
| Average Positive Month Return | 3.220 | 3.855 | 2.617 |
| Avereage Negative Month Return | -3.579 | -2.225 | -1.897 |
| Number of Negative Months | 100.000 | 112.000 | 102.000 |
| Number of Positive Months | 156.000 | 144.000 | 154.000 |
| Worst Drawdown | 54.029 | 20.216 | 25.903 |


| Statistic | S&P500 | PS Multi Strategy | PS Multi Strategy and S&P500 |
|---|---|---|---|
| Annualized Return | 12.890 | 13.060 | 13.310 |
| Annualized Sharpe (Rf=0%) | 1.139 | 1.270 | 1.770 |
| Annualized Std Dev | 11.320 | 10.290 | 7.520 |
| Average Positive Month Return | 2.794 | 2.771 | 2.159 |
| Avereage Negative Month Return | -2.385 | -1.891 | -1.328 |
| Number of Negative Months | 32.000 | 35.000 | 30.000 |
| Number of Positive Months | 64.000 | 61.000 | 66.000 |
| Worst Drawdown | 17.028 | 6.988 | 7.601 |
Combining a
to investing in commodities we create a product with
that gives superior risk adjusted returns.